Scientific.Signals.Models.AveragedAutoRegressiveModel

Package Scientific :: Package Signals :: Module Models :: Class AveragedAutoRegressiveModel |
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# Class AveragedAutoRegressiveModel

    AutoRegressiveModel --+
                          |
                         AveragedAutoRegressiveModel

Averaged auto-regressive model for stochastic process

An averaged model is constructed by averaging the model coefficients of several auto-regressive models of the same order. An averaged model is created empty, then individual models are added.

Instance Methods
__init__(self, order, delta_t) |
add(self, model, weight=1) Adds the coefficients of an autoregressive model to the average. |
Inherited from `AutoRegressiveModel`: `correlation`, `frictionConstant`, `memoryFunction`, `memoryFunctionZ`, `memoryFunctionZapprox`, `poles`, `predictStep`, `spectrum`

Method Details

### __init__(self, order, delta_t) (Constructor) |
Parameters: `order` (`int`) - the order of the model `delta_t` (`float`) - the sampling interval for the time series Overrides: AutoRegressiveModel.__init__

### add(self, model, weight=1) |
Adds the coefficients of an autoregressive model to the average. Parameters: `model` (AutoRegressiveModel) - an autoregressive model `weight` (`float`) - the weight of the model in the average Raises: `ValueError` - if the order of the model does not match the order of the average model